Scientists at Mount Sinai’s Icahn School of Medicine have developed an artificial intelligence platform that can detect Alzheimer’s and other neurodegenerative diseases including chronic traumatic encephalopathy with a high degree of accuracy.

The artificial intelligence platform, the Precise Informatics Platform, has been shown to be highly effective at diagnosing features of Alzheimer’s disease and other neurodegenerative diseases in brain tissue samples. The researchers trained the AI system to identify abnormal tau proteins in neurofibrillary tangles in brain samples, which is indicative of Alzheimer’s disease. The abnormal tau proteins are also known to build up in other neurodegenerative diseases.

Powerful machine learning methods were used to assess digitized microscope images of brain tissue obtained from patients with a wide range of neurodegenerative diseases. The scientists created a neural network that was capable of identifying neurofibrillary tangles in digitized images with a high degree of accuracy.

Human analysis of brain tissue is required for a definitive diagnosis, but that process is time consuming and requires specialists in neurodegenerative diseases. Artificial intelligence systems have the potential to speed up the process of diagnosing diseases. While they are unlikely to replace trained disease specialists, they can help evaluate tissue samples and cut out much of the work.

“Utilizing artificial intelligence has great potential to improve our ability to detect and quantify neurodegenerative diseases, representing a major advance over existing labor-intensive and poorly reproducible approaches,” said John Crary, MD, PhD, Professor of Pathology and Neuroscience at Icahn School of Medicine at Mount Sinai.

It is hoped that the platform will allow researchers develop targeted biomarkers that will help neuropathologists diagnose neurodegenerative diseases faster and with greater accuracy, which will ultimately improve patient outcomes.

Further information on the AI system can be found in the paper – Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy– which was published in the journal Laboratory Investigation in February. DOI: 10.1038/s41374-019-0202-4